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Published, Version of Record (VoR)CC BY V4.0, Open
Journal article
Sparse Firing in a Hybrid Central Pattern Generator for Spinal Motor Circuits
Neural computation, v 36(5), p759
23 Apr 2024
PMID: 38658025
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Central pattern generators are circuits generating rhythmic movements, such as walking. The majority of existing computational models of these circuits produce antagonistic output where all neurons within a population spike with a broad burst at about the same neuronal phase with respect to network output. However, experimental recordings reveal that many neurons within these circuits fire sparsely, sometimes as rarely as once within a cycle. Here we address the sparse neuronal firing and develop a model to replicate the behavior of individual neurons within rhythm-generating populations to increase biological plausibility and facilitate new insights into the underlying mechanisms of rhythm generation. The developed network architecture is able to produce sparse firing of individual neurons, creating a novel implementation for exploring the contribution of network architecture on rhythmic output. Furthermore, the introduction of sparse firing of individual neurons within the rhythm-generating circuits is one of the factors that allows for a broad neuronal phase representation of firing at the population level. This moves the model toward recent experimental findings of evenly distributed neuronal firing across phases among individual spinal neurons. The network is tested by methodically iterating select parameters to gain an understanding of how connectivity and the interplay of excitation and inhibition influence the output. This knowledge can be applied in future studies to implement a biologically plausible rhythm-generating circuit for testing biological hypotheses.
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Details
- Title
- Sparse Firing in a Hybrid Central Pattern Generator for Spinal Motor Circuits
- Creators
- Beck Strohmer - Technical University of DenmarkElias Najarro - IT University of CopenhagenJessica Ausborn - Drexel UniversityRune W Berg - University of CopenhagenSilvia Tolu - Technical University of Denmark
- Publication Details
- Neural computation, v 36(5), p759
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Neurobiology and Anatomy
- Web of Science ID
- WOS:001208570100008
- Scopus ID
- 2-s2.0-85191382409
- Other Identifier
- 991021871370904721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Neurosciences